A Bayesian approach to diagram matching with application to architectural models.

IT system architectures, as well as other systems, are often described by formal models or informal diagrams. In practice, there are often a number of versions of a model, e.g. for different views of a system, divergent variants, or a series of revisions. Understanding how versions of a model correspond or differ is crucial, yet little work has been done on automated assistance for matching models and diagrams.We have designed a framework based on Bayesian methods for finding these correspondences automatically. We represent models and diagrams as graphs whose nodes have attributes such as name, type, connections, and containment relations, and we have developed probabilistic models for rating the quality of candidate correspondences based on various features of the nodes in the graphs. Given the probabilistic models, we can find high quality correspondences using search algorithms. Preliminary experiments focusing on architectural models suggest that the technique is promising.